MTS - Infrastructure
Company websiteomnifold.ai (Omnifold, opens in new tab)
Base salary $150K to $300K
Employer-published annual base salary, USD. Advertised base range in San Francisco, CA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSan Francisco, CA
- WorkplaceOn-site
- Status at last checkSource accepting applications when checked
- Last checked (44 min ago) · observed since
About this job
Infrastructure Team
Omnifold trains custom AI models that help planners forecast the future. We are hiring for our Infrastructure Team, who own the systems that make everything else possible.
What makes this job interesting:
We train a unique model for each customer, which means model training and inference work differently here than at any other company. You’ll never get more reps building model training infrastructure!
Our team has very fast iteration speed but needs robust monitoring to pick up signal on user patterns. This is especially important as our application interface for AI-driven forecasting is unique on the market.
What you’ll own
Deployment: Reliable processes for getting models and services into production
Security: Data isolation between customers, product security, infrastructure hardening (SOC2 compliance and beyond)
Cloud resource management: GPU allocation, instance sizing, cost optimization
Monitoring and logging: Visibility into what's running, what's failing, and why
Data and ML ops: ETL pipelines from varied customer data sources, model versioning and lifecycle management
Automated testing: Building the test infrastructure that lets us ship with confidence
What we’re looking for
Experience with cloud computing (especially GPU workloads), CI/CD infrastructure-as-code. We run on AWS
Familiarity with or interest in ML workflows
Security fundamentals: encryption, access controls, compliance basics
Python proficiency
Must have a strong Computer Science background
Location: San Francisco (in-person, 5 days per week)
Omnifold’s Mission
Every bad forecast has a physical consequence. Unnecessary goods are manufactured, shipped, and stored. Emergency air freight is needed for misallocated products. Poor production planning means workers show up with nothing to do, or work frantic overtime. Inefficiency is everywhere.
Our mission is to eliminate waste and accelerate growth for every company with physical products.
Compensation: $150K to $300K base | Equity | Health, dental, vision | 401(k)
Source: Omnifold on Ashby · View original posting (opens in new tab)
This listingMTS - Infrastructure$150K to $300K
MTS - ML Research Scientist$150K to $300K
Applied AI$150K to $300K
MTS - Applications$150K to $300K
Director of Applied AI$200K to $300K
Chart as a table
| Role | Published base |
|---|---|
| MTS - Infrastructure (this listing) | $150K - $300K |
| MTS - ML Research Scientist | $150K - $300K |
| Applied AI | $150K - $300K |
| MTS - Applications | $150K - $300K |
| Director of Applied AI | $200K - $300K |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-03-11
Where this pay comes from
Location as the employer wrote it: San Francisco HQ
Compensation: $150K to $300K base | Equity | Health, dental, vision | 401(k)
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.